---
license: apache-2.0
base_model: google/electra-base-discriminator
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: electra_multiple_choice
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# electra_multiple_choice

This model is a fine-tuned version of [google/electra-base-discriminator](https://huggingface.co/google/electra-base-discriminator) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.6404
- Accuracy: 0.4

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 5e-06
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 100

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 1.4566        | 1.0   | 1724  | 1.3690          | 0.3      |
| 1.2925        | 2.0   | 3448  | 1.3269          | 0.4      |
| 1.1812        | 3.0   | 5172  | 1.3479          | 0.35     |
| 1.0807        | 4.0   | 6896  | 1.3464          | 0.35     |
| 0.9799        | 5.0   | 8620  | 1.3757          | 0.4      |
| 0.8792        | 6.0   | 10344 | 1.5018          | 0.45     |
| 0.7843        | 7.0   | 12068 | 1.6404          | 0.4      |


### Framework versions

- Transformers 4.31.0
- Pytorch 2.0.1+cu117
- Datasets 2.14.4
- Tokenizers 0.13.3